Grade II and III Oligodendroglioma and Astrocytoma

The impact of gliomas on the normal brain microenvironment: a pilot study

Gliomas are malignant tumors of neuronal support cells within the central nervous system (CNS) and are characterized by poor overall prognoses and limited treatment options due to their infiltrative growth patterns. The neural tumor microenvironment, composed of benign neurons, neuroglia, endothelial cells, and intravascular white blood cells, is a target-rich site for potential chemotherapeutic agents. This study assessed cell proliferation rates, white blood cell components, and a limited number of nuclear, cytoplasmic, and membrane markers using immunohistochemistry (IHC) assays on formalin-fixed and paraffin-embedded benign and glial tumor tissue samples from the CNS. It was observed that glioma tissues had increased rates of glial cell proliferation and significant increases in the number of observed T-lymphocytes and granulocytes but decreased expression of markers Somatostatin receptor 2 (SSTR2), L1 cell adhesion molecule (L1CAM), and GATA binding protein 3 (GATA3) when compared to benign tissue samples. Understanding the lack of protein expression and population expansion potential of the glioma microenvironment in greater detail could help identify valuable therapeutic target combinations for future treatments.

Toxicological insights and safety considerations of vorasidenib in grade 2 astrocytoma and oligodendroglioma

Vorasidenib, a dual inhibitor of isocitrate dehydrogenase 1 and 2 (IDH1/2), has shown promise as a therapeutic agent following its recent FDA approval for the treatment of grade 2 astrocytomas and oligodendrogliomas harboring IDH mutations in patients 12 years of age and older following surgery. While Vorasidenib offers significant potential in targeting altered metabolic pathways in low-grade gliomas, its comprehensive toxicologic and safety profile has not been adequately explored. This research letter addresses this critical gap by presenting an in silico analysis of the potential toxicologic effects of Vorasidenib. Using computational tools - ADMETlab 3.0, FAF-Drugs 4.1, DeepPK, vNN-ADMET, Pred-hERG 5.0, ADVERPred, PreADMET, and ADMET-AI - and databases such as ChEMBL, PubChem, and ChemSpider, we evaluated the key physicochemical properties and predicted ADMET profiles of Vorasidenib, along with a comparative analysis of two other drugs, namely Ivosidenib and Enasidenib. Our results suggest potential risks associated with drug-induced liver injury (DILI) and hepatotoxicity, with structural properties indicative of hepatocellular damage during and after treatment. The low clearance rates associated with the low maximum recommended dose suggest that Vorasidenib may accumulate in the bloodstream over time, increasing the likelihood of toxic reactions. In addition, the predictive models indicate concerns for neurotoxicity, nephrotoxicity and cardiotoxicity, including potential blockade of hERG channels leading to QT interval prolongation and cardiac arrhythmias. Importantly, the analysis also indicates risks of genotoxicity and carcinogenicity, raising concerns about promoting additional tumor formation in patients already prone to malignancies. These results emphasize the need for further preclinical and clinical studies to validate the safety of Vorasidenib. A comprehensive understanding of the toxicologic profile is critical to ensure that the therapeutic benefit for patients with IDH1/2-mutated low-grade gliomas is not compromised by potential adverse effects. Careful monitoring of patients and tailored therapeutic strategies are essential to optimize clinical outcomes and guide physicians in the safe use of Vorasidenib in clinical practice.

Exploring adult glioma through MRI: A review of publicly available datasets to guide efficient image analysis

Background

Publicly available data are essential for the progress of medical image analysis, in particular for crafting machine learning models. Glioma is the most common group of primary brain tumors, and magnetic resonance imaging (MRI) is a widely used modality in their diagnosis and treatment. However, the availability and quality of public datasets for glioma MRI are not well known.

Methods

In this review, we searched for public datasets of glioma MRI using Google Dataset Search, The Cancer Imaging Archive, and Synapse.

Results

A total of 28 datasets published between 2005 and May 2024 were found, containing 62 019 images from 5515 patients. We analyzed the characteristics of these datasets, such as the origin, size, format, annotation, and accessibility. Additionally, we examined the distribution of tumor types, grades, and stages among the datasets. The implications of the evolution of the World Health Organization (WHO) classification on tumors of the brain are discussed, in particular the 2021 update that significantly changed the definition of glioblastoma.

Conclusions

Potential research questions that could be explored using these datasets were highlighted, such as tumor evolution through malignant transformation, MRI normalization, and tumor segmentation. Interestingly, only 2 datasets among the 28 studied reflect the current WHO classification. This review provides a comprehensive overview of the publicly available datasets for glioma MRI currently at our disposal, providing aid to medical image analysis researchers in their decision-making on efficient dataset choice.

Cerebrospinal Fluid Liquid Biopsies in the Evaluation of Adult Gliomas

PURPOSE OF REVIEW

This review aims to discuss recent research regarding the biomolecules explored in liquid biopsies and their potential clinical uses for adult-type diffuse gliomas.

RECENT FINDINGS

Evaluation of tumor biomolecules via cerebrospinal fluid (CSF) is an emerging technology in neuro-oncology. Studies to date have already identified various circulating tumor DNA, extracellular vesicle, micro-messenger RNA and protein biomarkers of interest. These biomarkers show potential to assist in multiple avenues of central nervous system (CNS) tumor evaluation, including tumor differentiation and diagnosis, treatment selection, response assessment, detection of tumor progression, and prognosis. In addition, CSF liquid biopsies have the potential to better characterize tumor heterogeneity compared to conventional tissue collection and CNS imaging. Current imaging modalities are not sufficient to establish a definitive glioma diagnosis and repeated tissue sampling via conventional biopsy is risky, therefore, there is a great need to improve non-invasive and minimally invasive sampling methods. CSF liquid biopsies represent a promising, minimally invasive adjunct to current approaches which can provide diagnostic and prognostic information as well as aid in response assessment.

WD repeat domain 76 predicts poor prognosis in lower grade glioma and provides an original target for immunotherapy

BACKGROUND

The WD40 repeat (WDR) domain provides scaffolds for numerous protein-protein interactions in multiple biological processes. WDR domain 76 (WDR76) has complex functionality owing to its diversified interactions; however, its mechanism in LGG has not yet been reported.

METHODS

Transcriptomic data from public databases were multifariously analyzed to explore the role of WDR76 in LGG pathology and tumor immunity. Laboratory experiments were conducted to confirm these results.

RESULTS

The results first confirmed that high expression of WDR76 in LGG was not only positively associated with clinical and molecular features of malignant LGG, but also served as an independent prognostic factor that predicted shorter survival in patients with LGG. Furthermore, high expression of WDR76 resulted in the upregulation of oncogenes, such as PRC1 and NUSAP1, and the activation of oncogenic mechanisms, such as the cell cycle and Notch signaling pathway. Finally, WDR76 was shown to be involved in LGG tumor immunity by promoting the infiltration of immune cells, such as M2 macrophages, and the expression of immune checkpoints, such as PDCD1 (encoding PD-1).

CONCLUSIONS

This study shows for the first time the diagnostic and prognostic value of WDR76 in LGG and provides a novel personalized biomarker for future targeted therapy and immunotherapy. Thus, WDR76 may significantly improve the prognosis of patients with LGG.

Antiangiogenic exclusion rules in glioma trials: Historical perspectives and guidance for future trial design

Background

Despite the lack of proven therapies for recurrent high-grade glioma (HGG), only 8%-11% of patients with glioblastoma participate in clinical trials, partly due to stringent eligibility criteria. Prior bevacizumab treatment is a frequent exclusion criterion, due to difficulty with response assessment and concerns for rebound edema following antiangiogenic discontinuation. There are no standardized trial eligibility rules related to prior antiangiogenic use.

Methods

We reviewed ClinicalTrials.gov listings for glioma studies starting between May 2009 and July 2022 for eligibility rules related to antiangiogenics. We also reviewed the literature pertaining to bevacizumab withdrawal.

Results

Two hundred and ninety-seven studies for patients with recurrent glioma were reviewed. Most were phase 1 (n = 145, 49%), non-randomized (n = 257, 87%), evaluated a drug-only intervention (n = 223, 75%), and had a safety and tolerability primary objective (n = 181, 61%). Fifty-one (17%) excluded participants who received any antiangiogenic, one (0.3%) excluded participants who received any non-temozolomide systemic therapy. Fifty-nine (20%) outlined washout rules for bevacizumab (range 2-24 weeks, 4-week washout n = 35, 12% most common). Seventy-eight required a systemic therapy washout (range 1-6 weeks, 4-week washout n = 34, 11% most common). Nine permitted prior bevacizumab use with limitations, 18 (6%) permitted any prior bevacizumab, 5 (2%) were for bevacizumab-refractory disease, and 76 (26%) had no rules regarding antiangiogenic use. A literature review is then presented to define standardized eligibility criteria with a 6-week washout period proposed for future trial design.

Conclusions

Interventional clinical trials for patients with HGG have substantial heterogeneity regarding eligibility criteria pertaining to bevacizumab use, demonstrating a need for standardizing clinical trial design.

Contribution of whole slide imaging-based deep learning in the assessment of intraoperative and postoperative sections in neuropathology

The pathological diagnosis of intracranial germinoma (IG), oligodendroglioma, and low-grade astrocytoma on intraoperative frozen section (IFS) and hematoxylin-eosin (HE)-staining section directly determines patients' treatment options, but it is a difficult task for pathologists. We aimed to investigate whether whole-slide imaging (WSI)-based deep learning can contribute new precision to the diagnosis of IG, oligodendroglioma, and low-grade astrocytoma. Two types of WSIs (500 IFSs and 832 HE-staining sections) were collected from 379 patients at multiple medical centers. Patients at Center 1 were split into the training, testing, and internal validation sets (3:1:1), while the other centers were the external validation sets. First, we subdivided WSIs into small tiles and selected tissue tiles using a tissue tile selection model. Then a tile-level classification model was established, and the majority voting method was used to determine the final diagnoses. Color jitter was applied to the tiles so that the deep learning (DL) models could adapt to the variations in the staining. Last, we investigated the effectiveness of model assistance. The internal validation accuracies of the IFS and HE models were 93.9% and 95.3%, respectively. The external validation accuracies of the IFS and HE models were 82.0% and 76.9%, respectively. Furthermore, the IFS and HE models can predict Ki-67 positive cell areas with R² of 0.81 and 0.86, respectively. With model assistance, the IFS and HE diagnosis accuracy of pathologists improved from 54.6%-69.7% and 53.5%-83.7% to 87.9%-93.9% and 86.0%-90.7%, respectively. Both the IFS model and the HE model can differentiate the three tumors, predict the expression of Ki-67, and improve the diagnostic accuracy of pathologists. The use of our model can assist clinicians in providing patients with optimal and timely treatment options.

Secondary cerebellopontine angle oligodendroglioma after cranial irradiation: a case report and literature review

PURPOSE/AIM

Cerebellopontine angle (CPA) oligodendrogliomas are very rare, and only three preoperative cases have been confirmed. Secondary CPA oligodendrogliomas after radiation therapy are exceptionally rare, and no other cases have been reported.

CASE REPORT

We present a case of a 25-year-old male with CPA oligodendroglioma who experienced hearing loss in right ear with walking instability for more than 2 months. The patient underwent craniotomy in our hospital because of grade II astrocytoma of the right temporal lobe 10 years ago. Postoperative radiotherapy lasted for 30 days, and six rounds of chemotherapy were performed. Magnetic resonance imaging (MRI) of the head revealed a cystic lesion located in the right CPA. The patient underwent surgery without obvious complications, and the tumor was subtotally removed. Histopathological examination revealed a diagnosis of oligodendroglioma, World Health Organization (WHO) grade II. The patient was discharged on the tenth postoperative day with a good recovery. Two weeks after discharge, chemotherapy with temozolomide and radiotherapy were performed. The patient remained well at 8 months follow-up.

CONCLUSIONS

To the best of our knowledge, no other cases of secondary CPA oligodendroglioma after cranial irradiation have been reported in the literature. Compared with general oligodendroglioma, the tumor has no typical calcification and is more aggressive. The cranial nerves in the CPA area are closely adhered, and the blood supply is abnormally rich. It is difficult to completely remove the tumor. Postoperative radiotherapy and chemotherapy should be carried out as soon as possible.

Natural and synthetic compounds for glioma treatment based on ROS-mediated strategy

Glioma is the most frequent and most malignant tumor of the central nervous system (CNS)，accounting for about 50% of all CNS tumor and approximately 80% of the malignant primary tumors in the CNS. Patients with glioma benefit from surgical resection, chemo- and radio-therapy. However these therapeutical strategies do not significantly improve the prognosis, nor increase survival rates owing to restricted drug contribution in the CNS and to the malignant characteristics of glioma. Reactive oxygen species (ROS) are important oxygen-containing molecules that regulate tumorigenesis and tumor progression. When ROS accumulates to cytotoxic levels, this can lead to anti-tumor effects. Multiple chemicals used as therapeutic strategies are based on this mechanism. They regulate intracellular ROS levels directly or indirectly, resulting in the inability of glioma cells to adapt to the damage induced by these substances. In the current review, we summarize the natural products, synthetic compounds and interdisciplinary techniques used for the treatment of glioma. Their possible molecular mechanisms are also presented. Some of them are also used as sensitizers: they modulate ROS levels to improve the outcomes of chemo- and radio-therapy. In addition, we summarize some new targets upstream or downstream of ROS to provide ideas for developing new anti-glioma therapies.

An expanded role for surgery in grade 3 1p/19q co-deleted oligodendroglioma

Background

Grade 3 1p/19q co-deleted oligodendroglioma is an uncommon primary CNS tumor with a high rate of progression and recurrence. This study examines the benefit of surgery after progression and identifies predictors of survival.

Methods

This is a single-institution retrospective cohort study of consecutive adult patients with anaplastic or grade 3 1p/19q co-deleted oligodendroglioma diagnosed between 2001 and 2020.

Results

Eighty patients with 1p/19q co-deleted grade 3 oligodendroglioma were included. The median age was 47 years (interquartile range 38-56) and 38.8% were women. All patients underwent surgery, including gross total resection (GTR) for 26.3% of patients, subtotal resection (STR) for 70.0% of patients, and biopsy for 3.8% of patients. Forty-three cases (53.8%) progressed at a median of 5.6 years, and the median overall survival (OS) was 14.1 years. Among 43 cases of progression or recurrence, 21 (48.8%) underwent another resection. Patients who underwent a second operation had improved OS (P = .041) and survival after progression/recurrence (P = .012), but similar time to subsequent progression as patients who did not have repeat surgery (P = .50). Predictors of mortality at initial diagnosis included a preoperative Karnofsky Performance Status (KPS) under 80 (hazard ratio [HR] 5.4; 95% CI 1.5-19.2), an STR or biopsy rather than GTR (HR 4.1; 95% CI 1.2-14.2), and a persistent postoperative neurologic deficit (HR 4.0; 95% CI 1.2-14.1).

Conclusions

Repeat surgery is associated with increased survival, but not time to subsequent progression for progressing or recurrent 1p/19q co-deleted grade 3 oligodendrogliomas recur. Mortality is associated with a preoperative KPS under 80, lack of GTR, and persistent postoperative neurologic deficits after the initial surgery.

Simple approach for the histomolecular diagnosis of central nervous system gliomas based on 2021 World Health Organization Classification

The classification of central nervous system (CNS) glioma went through a sequence of developments, between 2006 and 2021, started with only histological approach then has been aided with a major emphasis on molecular signatures in the 4th and 5th editions of the World Health Organization (WHO). The recent reformation in the 5th edition of the WHO classification has focused more on the molecularly defined entities with better characterized natural histories as well as new tumor types and subtypes in the adult and pediatric populations. These new subclassified entities have been incorporated in the 5^th edition after the continuous exploration of new genomic, epigenomic and transcriptomic discovery. Indeed, the current guidelines of 2021 WHO classification of CNS tumors and European Association of Neuro-Oncology (EANO) exploited the molecular signatures in the diagnostic approach of CNS gliomas. Our current review presents a practical diagnostic approach for diffuse CNS gliomas and circumscribed astrocytomas using histomolecular criteria adopted by the recent WHO classification. We also describe the treatment strategies for these tumors based on EANO guidelines.

Machine Learning-Based Integration Develops a Pyroptosis-Related lncRNA Model to Enhance the Predicted Value of Low-Grade Glioma Patients

Background

Molecular features have been included in the categorization of gliomas because they may be excellent predictors of tumor prognosis. Lower-grade glioma (LGGs, which comprise grade 2 and grade 3 gliomas) patients have a wide variety of outcomes. The goal of this research is to investigate a pyroptosis-based long noncoding RNA (lncRNA) profile and see whether it can be used to predict LGG prognosis.

Methods

The Genotype-Tissue Expression (GTEx) and Cancer Genome Atlas (TCGA) datasets were utilized to get RNA data and clinical information for this research. Six considerably related lncRNAs (AL355574.1, AL355974.2, Z97989.1, SNAI3-AS1, LINC02593, and CYTOR) were selected using Cox regression (univariate and multivariate) and LASSO Cox regression. A variety of statistical techniques, including ROC curves, nomogram, and Kaplan-Meier curves, were utilized to verify the risk score's accuracy. Following that, bioinformatics studies were carried out to investigate the possible molecular processes that influence LGG prognosis. The variations in pathway enrichment were investigated using GSEA. The immune microenvironment inconsistencies were investigated using CIBERSORT, ESTIMATE, MCPcounter, TIMER algorithms, and ssGSEA.

Results

We discovered six lncRNAs with distinct expression patterns that are linked to LGG prognosis. Kaplan-Meier studies showed a signature of high-risk lncRNAs associated with a poor prognosis for LGG. Furthermore, the AUC of the lncRNA signature was 0.763, indicating that they may be used to predict LGG prognosis. In predicting LGG prognosis, our risk assessment approach outperformed conventional clinicopathological characteristics. In the high-risk group of people, GSEA identified tumor-related pathways and immune-related pathways. Furthermore, T cell-related activities such as T cell coinhibition and costimulation, check point, APC coinhibition and costimulation, CCR, and inflammatory promoting were shown to be substantially different between the two groups in TCGA analysis. Immune checkpoints including PD-1, CTLA4, and PD-L1 were expressed differentially in the two groups as well.

Conclusion

This study found that pyroptosis-based lncRNAs were useful in predicting LGG patients' survival, suggesting that they may be used as a therapeutic target in the future.

Recurrence of an Oligodendroglioma in an Anaplastic Form – Case Report and Short Literature Review

Oligodendrogliomas are a rare diffuse astrocytic tumor, usually present in young adults, which depending on the pathogenic alterations can lead to major disabilities or even death. We present a case of a male patient in the fifth decade of life, who initially presented with an oligodendroglioma, and approximately one year after the first therapeutic intervention the condition recurred in the form of an anaplastic oligodendroglioma. We made a complete histopathological and immunohistochemical panel in order to have a final diagnosis with the greatest accuracy, thus making a comparison with the literature in order to assess the diagnosis and subsequent therapeutic conduct.

The reliability and interobserver reproducibility of T2/FLAIR mismatch in the diagnosis of IDH-mutant astrocytomas

PURPOSE

The reliability and reproducibility of T2-weighted imaging/ fluid-attenuated inversion recovery (T2/FLAIR) mismatch were investigated in the diagnosis of isocitrate dehydrogenase (IDH) mutant astrocytoma between WHO grade II and III diffuse hemispheric gliomas.

METHODS

WHO grade II and grade III diffuse hemispheric gliomas (n=133) treated in our institute were included in the study. Pathological findings and molecular markers of the cases were reviewed with the criteria of WHO 2016. The finding of mismatch between T2-weighted and FLAIR images in preoperative magnetic resonance imaging (MRI) of the cases was evaluated by two different radiologists. The readers reviewed MRIs independently, blinded to the histopathologic diagnosis or molecular subset of tumors. The cases were classified as IDH-mutant astrocytoma, oligodendroglioma and IDH-wildtype (IDH-wt) astrocytoma according to molecular and genetic features.

RESULTS

T2/FLAIR mismatch positivity was observed in 46 patients (34.6%). T2/FLAIR mismatch positivity was observed in 42 of 75 IDH-mutant astrocytomas (56%) and 4 of 43 oligodendrogliomas (9.30%), while it was not seen among IDH-wt astrocytomas (0/15, 0%). The T2/FLAIR mismatch ratio was significantly different between IDH-mutant astrocytomas (WHO grade II and grade III) and oligodendrogliomas (chi-square, p <0.05). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of T2/FLAIR mismatch in predicting IDH-mutant astrocytomas were 58.7%, 90.7%, 91.7%, 61.4%, and 70.3% respectively. Radiologist 1 diagnosed T2/FLAIR mismatch in 48 of 133 cases (36.1%) and Radiologist 2 in 66 of 133 cases (49.6%). The interrater agreement for the T2/FLAIR mismatch sign was 0.61 (p <0.05), 95% CI (0.55, 0.67).

CONCLUSION

T2/FLAIR mismatch appears to be an important MRI finding in distinguishing IDH-mutant astrocytomas from other diffuse hemispheric gliomas. However, it should be kept in mind that T2/FLAIR mismatch sign can be seen in a minority of oligodendrogliomas besides IDH-mutant astrocytomas.

Differentiation of Low-Grade Astrocytoma From Anaplastic Astrocytoma Using Radiomics-Based Machine Learning Techniques

Purpose

To investigate the diagnostic ability of radiomics-based machine learning in differentiating atypical low-grade astrocytoma (LGA) from anaplastic astrocytoma (AA).

Methods

The current study involved 175 patients diagnosed with LGA (n = 95) or AA (n = 80) and treated in the Neurosurgery Department of West China Hospital from April 2010 to December 2019. Radiomics features were extracted from pre-treatment contrast-enhanced T1 weighted imaging (T1C). Nine diagnostic models were established with three selection methods [Distance Correlation, least absolute shrinkage, and selection operator (LASSO), and Gradient Boosting Decision Tree (GBDT)] and three classification algorithms [Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and random forest (RF)]. The sensitivity, specificity, accuracy, and areas under receiver operating characteristic curve (AUC) of each model were calculated. Diagnostic ability of each model was evaluated based on these indexes.

Results

Nine radiomics-based machine learning models with promising diagnostic performances were established. For LDA-based models, the optimal one was the combination of LASSO + LDA with AUC of 0.825. For SVM-based modes, Distance Correlation + SVM represented the most promising diagnostic performance with AUC of 0.808. And for RF-based models, Distance Correlation + RF were observed to be the optimal model with AUC of 0.821.

Conclusion

Radiomic-based machine-learning has the potential to be utilized in differentiating atypical LGA from AA with reliable diagnostic performance.

Comparative evaluation of intracranial oligodendroglioma and astrocytoma of similar grades using conventional and T1-weighted DCE-MRI

PURPOSE

This retrospective study was performed on a 3T MRI to determine the unique conventional MR imaging and T1-weighted DCE-MRI features of oligodendroglioma and astrocytoma and investigate the utility of machine learning algorithms in their differentiation.

METHODS

Histologically confirmed, 81 treatment-naïve patients were classified into two groups as per WHO 2016 classification: oligodendroglioma (n = 16; grade II, n = 25; grade III) and astrocytoma (n = 10; grade II, n = 30; grade III). The differences in tumor morphology characteristics were evaluated using Z-test. T1-weighted DCE-MRI data were analyzed using an in-house built MATLAB program. The mean 90th percentile of relative cerebral blood flow, relative cerebral blood volume corrected, volume transfer rate from plasma to extracellular extravascular space, and extravascular extracellular space volume values were evaluated using independent Student's t test. Support vector machine (SVM) classifier was constructed to differentiate two groups across grade II, grade III, and grade II+III based on statistically significant features.

RESULTS

Z-test signified only calcification among conventional MR features to categorize oligodendroglioma and astrocytoma across grade III and grade II+III tumors. No statistical significance was found in the perfusion parameters between two groups and its subtypes. SVM trained on calcification also provided moderate accuracy to differentiate oligodendroglioma from astrocytoma.

CONCLUSION

We conclude that conventional MR features except calcification and the quantitative T1-weighted DCE-MRI parameters fail to discriminate between oligodendroglioma and astrocytoma. The SVM could not further aid in their differentiation. The study also suggests that the presence of more than 50% T2-FLAIR mismatch may be considered as a more conclusive sign for differentiation of IDH mutant astrocytoma.

Environmentally Self-Adaptative Nanocarriers Suppress Glioma Proliferation and Stemness via Codelivery of shCD163 and Doxorubicin

Gliomas-devastating intracranial tumors with a dismal outcome-are in dire need of innovative treatment. Although nanodrugs have been utilized as a target therapy for certain types of solid tumors, their therapeutic effects in gliomas are limited due to the complications of the systemic circulation, blood-brain barrier (BBB), and specific glioma environment. Thus, we aimed to establish a nanoliposome adaptable to different environments by codelivery of shCD163 and doxorubicin (DOX) to treat gliomas. In this study, we first synthesized pH-sensitive DSPE-cRGD-Hz-PEG₂₀₀₀ to form an environmentally self-adaptative nanoliposome (cRGD-DDD Lip) via a thin film method. We used in vitro BBB models, in vitro cell uptake experiments, and in vivo biodistribution assays to confirm the long circulation time and low cell uptake of the cRGD-DDD Lip as a result of the poly(ethylene glycol) (PEG) shell of cRGD-DDD Lip in the neutral pH systemic circulation. Moreover, the cRGD-DDD Lip bypassed the BBB and attached to the intracranial glioma following the removal of the PEG shell and the exposure of cRGD to the weakly acidic tumor microenvironment. We further assembled the shCD163/DOX@cRGD-DDD Lip through cRGD-DDD Lip loading of shCD163 and DOX. In vitro, cell proliferation and self-renewal of glioma cells were inhibited by the shCD163/DOX@cRGD-DDD Lip due to the toxicity of DOX and the suppression of shCD163 via the CD163 pathway. In vivo, the shCD163/DOX@cRGD-DDD Lip disturbed the progression of in situ gliomas by inhibiting the growth and stemness of glioma cells and prevented the recurrence of gliomas after resection. In conclusion, the cRGD-DDD Lip may be a promising nanodrug-loading platform to cope with different environments and the shCD163/DOX@cRGD-DDD Lip may potentially be a novel nanodrug for glioma therapy.

A Novel Four-Gene Signature Associated With Immune Checkpoint for Predicting Prognosis in Lower-Grade Glioma

The overall survival of patients with lower grade glioma (LGG) varies greatly, but the current histopathological classification has limitations in predicting patients’ prognosis. Therefore, this study aims to find potential therapeutic target genes and establish a gene signature for predicting the prognosis of LGG. CD44 is a marker of tumor stem cells and has prognostic value in various tumors, but its role in LGG is unclear. By analyzing three glioma datasets from Gene Expression Omnibus (GEO) database, CD44 was upregulated in LGG. We screened 10 CD44-related genes via protein–protein interaction (PPI) network; function enrichment analysis demonstrated that these genes were associated with biological processes and signaling pathways of the tumor; survival analysis showed that four genes (CD44, HYAL2, SPP1, MMP2) were associated with the overall survival (OS) and disease-free survival (DFS)of LGG; a novel four-gene signature was constructed. The prediction model showed good predictive value over 2-, 5-, 8-, and 10-year survival probability in both the development and validation sets. The risk score effectively divided patients into high- and low- risk groups with a distinct outcome. Multivariate analysis confirmed that the risk score and status of IDH were independent prognostic predictors of LGG. Among three LGG subgroups based on the presence of molecular parameters, IDH-mutant gliomas have a favorable OS, especially if combined with 1p/19q codeletion, which further confirmed the distinct biological pattern between three LGG subgroups, and the gene signature is able to divide LGG patients with the same IDH status into high- and low- risk groups. The high-risk group possessed a higher expression of immune checkpoints and was related to the activation of immunosuppressive pathways. Finally, this study provided a convenient tool for predicting patient survival. In summary, the four prognostic genes may be therapeutic targets and prognostic predictors for LGG; this four-gene signature has good prognostic prediction ability and can effectively distinguish high- and low-risk patients. High-risk patients are associated with higher immune checkpoint expression and activation of the immunosuppressive pathway, providing help for screening immunotherapy-sensitive patients.

Accelerated progression of IDH mutant glioma after first recurrence

BACKGROUND

Isocitrate dehydrogenase (IDH) mutant gliomas are a distinct subtype, reflected in the World Health Organization (WHO) 2016 revised diagnostic criteria. To inform IDH-targeting trial design, we sought to characterize outcomes exclusively within IDH mutant gliomas.

METHODS

We retrospectively analyzed 275 IDH mutant glioma patients treated at our institution. Progression was determined using low-grade glioma criteria from Response Assessment in Neuro-Oncology. We calculated survival statistics with the Kaplan-Meier method, and survival proportions were correlated with molecular, histologic, and clinical factors.

RESULTS

During a median follow-up of 6.4 years, 44 deaths (7.6%) and 149 first progression (PFS1) events (54.1%) were observed. Median PFS1 was 5.7 years (95% CI: 4.7-6.4) and OS was 18.7 years (95% CI: 12.2 y-not reached). Consistent with prior studies, we observed an association of grade, molecular diagnosis, and treatment with PFS1. Following the first progressive episode, 79 second progression events occurred during a median follow-up period of 4.1 years. Median PFS following an initial progressive event (PFS2) was accelerated at 3.1 years (95% CI: 2.1-4.1). PFS2 was a surrogate prognostic marker, identifying patients with poorer overall survival.

CONCLUSION

We report outcomes in a large cohort of IDH mutant glioma, providing a well-characterized historical control population for future clinical trial design. Notably, the interval between first and second recurrence (PFS2, 3.0 y) is shorter than time from diagnosis to first recurrence (PFS1, 5.7 y), evidence that these tumors clinically degenerate from an indolent course to an accelerated malignant phase. Thus, PFS2 represents a relevant outcome for trials investigating drug efficacy at recurrence.

ISL2 modulates angiogenesis through transcriptional regulation of ANGPT2 to promote cell proliferation and malignant transformation in oligodendroglioma

Oligodendroglioma is an important type of lower-grade glioma (LGG), which is a slowly progressing brain tumor. Many LGGs eventually transform into a more aggressive or malignant type. Enhanced angiogenesis is a characteristic of malignantly transformed oligodendroglioma (m-oligodendroglioma). However, the pathogenesis and signaling pathways associated with angiogenesis and proliferation in m-oligodendroglioma are not well understood. In this study, we identified that Insulin Gene Enhancer Protein (ISL2) and its angiogenic capacity were inversely related to survival according to LGG patient data from an online database, and this was further confirmed with pathological LGG patient samples, including malignantly transformed samples, by detecting the expression of ISL2, the angiogenic markers vascular endothelial growth factor (VEGFA) and CD31 and the proliferation marker Ki-67. We then established novel oligodendroglioma patient tumor-derived orthotopic xenograft mouse models and cell lines to verify the role of ISL2 in regulating angiogenesis to promote oligodendroglioma growth and malignant transformation. Furthermore, ISL2 regulated ANGPT2 transcription by binding to the ANGPT2 promoter. Then, ANGPT2, a downstream gene, activated angiogenesis through VEGFA to promote oligodendroglioma malignant transformation. Finally, combining AAV-ISL2-shRNA with temozolomide suppressed oligodendroglioma progression more effectively than either monotherapy in vivo and in vitro. Thus, hypoxia-induced ISL2 regulated ANGPT2, which subsequently induced angiogenesis to promote oligodendroglioma growth and malignant transformation. Malignancy was accompanied by worsened hypoxia inside the tumor mass, creating a positive feedback loop. In conclusion, this study suggests that ISL2 is a biomarker for oligodendroglioma progression and that anti-ISL2 therapy may offer a potential clinical strategy for treating m-oligodendroglioma.

Heme Oxygenase-1 in Central Nervous System Malignancies

Central nervous system tumors are the most common pediatric solid tumors and account for 20–25% of all childhood malignancies. Several lines of evidence suggest that brain tumors show altered redox homeostasis that triggers the activation of various survival pathways, leading to disease progression and chemoresistance. Among these pathways, heme oxygenase-1 (HO-1) plays an important role. HO-1 catalyzes the enzymatic degradation of heme with the simultaneous release of carbon monoxide (CO), ferrous iron (Fe²⁺), and biliverdin. The biological effects of HO-1 in tumor cells have been shown to be cell-specific since, in some tumors, its upregulation promotes cell cycle arrest and cellular death, whereas, in other neoplasms, it is associated with tumor survival and progression. This review focuses on the role of HO-1 in central nervous system malignancies and the possibility of exploiting such a target to improve the outcome of well-established therapeutic regimens. Finally, several studies show that HO-1 overexpression is involved in the development and resistance of brain tumors to chemotherapy and radiotherapy, suggesting the use of HO-1 as an innovative therapeutic target to overcome drug resistance. The following keywords were used to search the literature related to this topic: nuclear factor erythroid 2 p45-related factor 2, heme oxygenase, neuroblastoma, medulloblastoma, meningioma, astrocytoma, oligodendroglioma, glioblastoma multiforme, and gliomas.

Application of an Artificial Intelligence Algorithm to Prognostically Stratify Grade II Gliomas

(1) Background: Recently, it has been shown that the extent of resection (EOR) and molecular classification of low-grade gliomas (LGGs) are endowed with prognostic significance. However, a prognostic stratification of patients able to give specific weight to the single parameters able to predict prognosis is still missing. Here, we adopt classic statistics and an artificial intelligence algorithm to define a multiparametric prognostic stratification of grade II glioma patients. (2) Methods: 241 adults who underwent surgery for a supratentorial LGG were included. Clinical, neuroradiological, surgical, histopathological and molecular data were assessed for their ability to predict overall survival (OS), progression-free survival (PFS), and malignant progression-free survival (MPFS). Finally, a decision-tree algorithm was employed to stratify patients. (3) Results: Classic statistics confirmed EOR, pre-operative- and post-operative tumor volumes, Ki67, and the molecular classification as independent predictors of OS, PFS, and MPFS. The decision tree approach provided an algorithm capable of identifying prognostic factors and defining both the cut-off levels and the hierarchy to be used in order to delineate specific prognostic classes with high positive predictive value. Key results were the superior role of EOR on that of molecular class, the importance of second surgery, and the role of different prognostic factors within the three molecular classes. (4) Conclusions: This study proposes a stratification of LGG patients based on the different combinations of clinical, molecular, and imaging data, adopting a supervised non-parametric learning method. If validated in independent case studies, the clinical utility of this innovative stratification approach might be proved.

Ability of Radiomics in Differentiation of Anaplastic Oligodendroglioma From Atypical Low-Grade Oligodendroglioma Using Machine-Learning Approach

Objectives: To investigate the ability of radiomics features from MRI in differentiating anaplastic oligodendroglioma (AO) from atypical low-grade oligodendroglioma using machine-learning algorithms.

Methods: A total number of 101 qualified patients (50 participants with AO and 51 with atypical low-grade oligodendroglioma) were enrolled in this retrospective, single-center study. Forty radiomics features of tumor images derived from six matrices were extracted from contrast-enhanced T1-weighted (T1C) images and fluid-attenuation inversion recovery (FLAIR) images. Three selection methods were performed to select the optimal features for classifiers, including distance correlation, least absolute shrinkage and selection operator (LASSO), and gradient boosting decision tree (GBDT). Then three machine-learning classifiers were adopted to generate discriminative models, including linear discriminant analysis, support vector machine, and random forest (RF). Receiver operating characteristic analysis was conducted to evaluate the discriminative performance of each model.

Results: Nine predictive models were established based on radiomics features from T1C images and FLAIR images. All of the classifiers represented feasible ability in differentiation, with AUC more than 0.840 when combined with suitable selection method. For models based on T1C images, the combination of LASSO and RF classifier represented the highest AUC of 0.904 in the validation group. For models based on FLAIR images, the combination of GBDT and RF classifier showed the highest AUC of 0.861 in the validation group.

Conclusion: Radiomics-based machine-learning approach could potentially serve as a feasible method in distinguishing AO from atypical low-grade oligodendroglioma.

Increased incidence of second primary malignancy in patients with malignant astrocytoma: a population-based study

We identified patients diagnosed with malignant astrocytoma (MA) as the first of two or more primary malignancies between 1973 and 2015 from Surveillance, Epidemiology and End Results (SEER) database. Multiple primaries-standardized incidence ratio (MP-SIR) was calculated to quantitate the risk of second primary malignancy (SPM). We further identified the risk factors of developing SPM and factors affecting overall survival (OS) in MA patients with SPM. Our results revealed that overall risk of SPM among MA patients was significantly higher than that in general population (SIR: 1.09, 95% confidence interval (CI): 1–1.18, P<0.05). Specific sites where the risk of SPM increased included salivary gland, bone and joints, soft tissue including heart, brain, cranial nerves other nervous system, thyroid, acute non-lymphocytic leukemia and acute myeloid leukemia. Overall risk of SPM in patients aged ≤29 and 30–59 years significantly increased (4.34- and 1.41-fold respectively). Whereas patients aged ≥60 years had a significantly decreased risk of SPM. Patients in the group of latency at 36–59, 60–119 and ≥120 months carried significantly increased overall risk of SPM. Multivariate analysis revealed that age, race, marital status, WHO grade, differentiated grade of cancer tissues, latency was independent predictor of OS in MA patients with SPM, which were all selected into the nomogram. The calibration curve for probability of survival showed good agreement between prediction by nomogram and actual observation. In conclusion, MA survivors should be advised of their increased risk for developing certain cancers in their lifetime. Our study had clinical implications for the surveillance of MA survivors at risk of developing SPM.

Impact of 1p/19q codeletion status on extent of resection in WHO grade II glioma: Insights from a national cancer registry

OBJECTIVE

Traditionally, extent of resection (EOR) has been seen as a surgical parameter that can predict survival outcomes of surgically managed WHO grade II gliomas. The aim of this study was to evaluate if such an influence was potentially affected by 1p/19q codeletion status based on a national cancer registry.

PATIENT AND METHODS

All adults diagnosed with grade II gliomas between the years 2004 to 2014 were queried from the National Cancer Database (NCDB). The population was then divided based on 1p/19q codeletion status, and then Kaplan-Meier, univariate and multivariate Cox regression analyses were utilized to evaluate the prognostic effect of EOR.

RESULTS

In total, 1,498 grade II gliomas satisfied inclusion for analysis, with the 1p/19q non-codeleted in 705 (47%) cases, and codeletion in 793 (53%) cases. When the cohort was divided based on codeletion status, Kaplan-Meier modelling and univariate regression analyses indicated that gross total resection (GTR) was significantly associated with greater 5-overall survival (OS) in both 1p/19q non-codeleted and codeletion groups. Upon multivariate analysis which incorporated adjuvant therapy status, the significance of GTR was only retained in the 1p/19q non-codeletion group after post-hoc adjustment.

CONCLUSION

Our findings indicate that the survival impact of GTR in grade II gliomas may be affected by 1p/19q codeletion status within the first five years after surgery based on overall survival. Therefore, molecular diagnostics have potential clinical application in surgery outcomes, and validation of the reported findings will assist in surgical planning if such an association can be thoroughly established.

Evidence-Based Practice: Temozolomide Beyond Glioblastoma

PURPOSE OF REVIEW

Temozolomide is a first-line treatment for newly diagnosed glioblastoma. In this review, we will examine the use of temozolomide in other contexts for treating gliomas, including recurrent glioblastoma, glioblastoma in the elderly, diffuse low- and high-grade gliomas, non-diffuse gliomas, diffuse intrinsic pontine glioma (DIPG), ependymoma, pilocytic astrocytoma, and pleomorphic xanthoastrocytoma.

RECENT FINDINGS

Temozolomide improved survival in older patients with glioblastoma, anaplastic gliomas regardless of 1p/19q deletion status, and progressive ependymomas. Temozolomide afforded less toxicity and comparable efficacy to radiation in high-risk low-grade gliomas and to platinum-based chemotherapy in pediatric high-grade gliomas. The success of temozolomide in promoting survival has expanded beyond glioblastoma to benefit patients with non-glioblastoma tumors. Identifying practical biomarkers for predicting temozolomide susceptibility, and establishing complementary agents for chemosensitizing tumors to temozolomide, will be key next steps for future success.